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Found 8 papers, 4 papers with code
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing
We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models
In this paper, we explore the effects of language variants, data sizes, and fine-tuning task types in Arabic pre-trained language models.
Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation
We also define the task of multi-class Arabic grammatical error detection (GED) and present the first results on multi-class Arabic GED.
Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects
We present state-of-the-art results on morphosyntactic tagging across different varieties of Arabic using fine-tuned pre-trained transformer language models.
Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information
One reason for this is that in the tagging scheme for such languages, a complete POS tag is formed by combining tags from multiple tag sets defined for each morphosyntactic category.
The Bahrain Corpus: A Multi-genre Corpus of Bahraini Arabic
Our objective is to create a specialized corpus of the Bahraini Arabic dialect, which includes written texts as well as transcripts of audio files, belonging to a different genre (folktales, comedy shows, plays, cooking shows, etc.).
Camelira: An Arabic Multi-Dialect Morphological Disambiguator
We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levantine.
